006 160719 urban environment analysis for new and existing neighborhood
TRANSCRIPT
NTNU-SJTU 2016 SEniC Summer School
NTNU Teacher Team, Monday 18.07.2016
Urban Environmental Analysis for New and Existing Neighborhood Case studies and Experiences
Example of an interdisciplinary approach
Gabriele Lobaccaro Postdoctoral Research Fellow
EU Energy Roadmap 2050
0 CLIMATE
Luca Finocchiaro
Luca Finocchiaro
Luca Finocchiaro
Luca Finocchiaro
Luca Finocchiaro Luca Finocchiaro
Luca Finocchiaro Luca Finocchiaro Luca Finocchiaro
Luca Finocchiaro
Luca Finocchiaro
1 Solar Potential
The total solar energy absorbed from the earth is equal:
3,850,000 EJ
The use of primary energy in 2009 was equal to:
510 EJ
Electricity:
62EJ
Energy Unused
International research activities
SUBTASK C: Case studies and action research Lead: Gabriele Lobaccaro and Carmel Lindkvist, NTNU, Norway
Solar Radiation vs Orography
2 Solar Reflections
20 Fenchurch Street - London
20 Fenchurch Street - London
20 Fenchurch Street - London
Palazzo della Regione Lombardia - Milan
Case study - Milan
Generative parametric solar optimization process
Solar irradiation simulations- District analyses Considering the surrounding (mutual reflections)
3 Overshadowing
effect
The empire state building- NYC
Burj Khalifa - Dubai
Simulation criteria and design strategies for solar availability Use of dynamic simulation tools for case studies of urban planning
Clara Good - Gabriele Lobaccaro PhD Candidate - Postdoctoral research fellow
Department of Architectural Design, History and Technology
Siri Hårklau Master student
Department of Electric Power Engineering
IEA TASK 51 “Solar Energy in Urban Planning”
Subtask C - Case study
Localization of the area
Lerkendal district
NTNU
Gløshaugens
Campus
Lerkendal district
Trondheim Centre
N
View of the area from the top - Source: google maps
Surrounding environment
Lerkendal district - Stadium
Top view from the East side - Source: http://www.info-stades.fr/
Solar Radiation in Norway Trondheim case study ZEB/BiPV commercial building
View from the North side - Photo: Gabriele Lobaccaro
Solar Radiation in Norway Trondheim case study ZEB/BiPV commercial building
Data
• Total building area approx . 11000 m2 of which 7,300 m2;
• Annual consumption not more than 84 kWh/m2 must
meet energy class A.
• The building is connected to district heating plants ,
power grids and also has its own production of electricity
in a solar system.
Solar System
• 203 m2 on the south and west facades, 27.2 kWp, 9
strings;
• The estimated annual production of approx. 18,000 kWh;
• Actual production in 2013 approx . 15,000 kWh. 15%
higher than simulated.
Source: http://tronderenergi.no/
Surrounding environment
Lerkendal district - Trondheim case study
View before the construction of the Lerkendal Studentby - Source: http://lerkendalblogg.skanska.no/
Solar Radiation in Norway
Lerkendal Studenby
Rendering and model of the district Masterplan of the new student houses
Source: https://www.arkitektur.no/lerkendal-studentby
Solar Radiation in Norway
Lerkendal studentby
Different design solutions
Source: https://www.arkitektur.no/lerkendal-studentby
Solar Radiation in Norway – Trondheim case study Lerkendal district
View from the Tower Hotel - Source: http://www.skyscrapercity.com/
Surrounding environment
Lerkendal district
View from the South side - Photo: Gabriele Lobaccaro
Surrounding environment
Tower Hotel
View from the North side - Photo: Gabriele Lobaccaro
Solar Radiation in Norway - Trondheim case study Overshadowing effect - Lack of preliminary study
View from the South side - Photo: Gabriele Lobaccaro
Solar Radiation in Norway - Trondheim case study Overshadowing effect - Lack of preliminary study
View from the Tower Hotel - Source: http://www.adressa.no/
Solar Radiation in Norway - Trondheim case study Overshadowing effect - Lack of preliminary study
View from inside the Lerkendal Studentby - Photo: Gabriele Lobaccaro
Methodology of Analysis using dynamic simulation tools
Level of simulation
1: Local solar potential
(isolated scenario)
2: Influence from surroundings
(context scenario)
3: Evaluate solar technologies based on
energy demand
DiVA for Rhino Based on Radiance
ray-tracing method
Pvsyst
PV simulation
Polysun
Solar thermal
Source: Presentation from RERC 2014 presentation - Author: Clara Good
Solar Radiation in Norway - Trondheim case study
Solar Mapping Analysis - Context scenario (entire building envelope)
View from inside the Lerkendal Studentby - Author: Gabriele Lobaccaro
Scenario Surface [m2]
Direct
radiation
[kWh/yr]
Global
radiation
[kWh/yr]
Context
scenario 5591.38 1416210.24 3261902.7
- 20% of direct radiation
- 11.5% of global radiation
N
Compare to the isolated scenario
Solar Radiation in Norway - Trondheim case study
Solar Mapping Analysis - Context scenario (South Façade and PV part)
Scenario
Surface South
Facade [m2]
Direct
radiation
[kWh/yr]
Global
radiation
[kWh/yr]
Context
scenario 665 (entire) 232386 430666
Context
scenario
194.5 (only PV
part in blue) 68626 124007
- 49% of direct radiation for PV systems
- 50% of direct radiation for South Facade
- 42% of global radiation for PV systems
- 40% of global radiation for South Facade
+ 7% of solar reflection contribution
+ 10% of solar reflection contribution
Simulation analysis - Author: Gabriele Lobaccaro
N
Compare to the isolated scenario
Source: Presentation from RERC 2014 presentation - Author: Clara Good
Area B
Design criterion: Same system area (200 m2)
Least affected areas Localization of the most irradiated areas
Output from area A
(facade) has more
even profile
Solar energy output Area A – Façade
Source: Presentation from RERC 2014 presentation - Author: Clara Good
Output from area B
(roof) peaks in
summer
Solar energy output Area B - Roof
Source: Presentation from RERC 2014 presentation - Author: Clara Good
Percentage of energy demand Comparison among systems
Source: Presentation from RERC 2014 presentation - Author: Clara Good
PV covers 3-6% of electricity demand
Solar thermal covers 21-26% of thermal demand
4 High temperature
Green actions and design solutions to mitigate heat wave risk in the city of Bilbao
Gabriele Lobaccaro with collaboration: Acero Juan Angel (Tecnalia)
Postdoctoral research fellowship Faculty of Architecture and Fine Art NTNU Group: Annemie Wyckmans, Naia Landa (KTH), Fernanda Pacheco, James Kallaos, NTNU Norwegian University of Science and Technology Krishna Bharathi
70
8th December 2015 - Berchem
71
FP7 EU RAMSES
Reconciling Adaptation, Mitigation and Sustainable Development for Cities
http://www.ramses-cities.eu/
Reconciling Adaptation, Mitigation and Sustainable Development for Cities
Extract of the plan of the “Anillo verde de Bilbao”: in green the routes of “Gran Recorrido de Bilbao, in red the auxiliary routes and
in blue the path of the “Cammino di Santiago”.
Connection between the green belt and city parks
72 Source: http://www.bilbao.net/
Compact Midrise
Compact Lowrise
Casco Viejo
Abando/Indautxu
Open-set Highrise
Txurdinaga
Reconciling Adaptation, Mitigation and Sustainable Development for Cities
Connection between the green belt and city parks
HOW
Reduction of the heat wave risk in the city of Bilbao
73
Reconciling Adaptation, Mitigation and Sustainable Development for Cities
Analysis of the Urban Areas
1 N
Analysis of the built areas in the districts of Casco Viejo (compact lowrise), Abando/Indautxu (compact midrise) and the Txurdinaga (open-set highrise).
Analysis of the streets in the districts of Casco Viejo (compact lowrise), Abando/Indautxu (compact midrise) and the Txurdinaga (open-set highrise).
74
75
Reconciling Adaptation, Mitigation and Sustainable Development for Cities
Analysis of the Urban Areas
1 N
Category Urban Areas Height Width H/W Façades mat. Roofs mat. Soil
Compact lowrise
Casco Viejo 16 m 4.5 m 3.5 concrete/brick/stone terracotta brick/stone
Compact midrise
Abando / Indautxu
24 m 16 m 1.5 concrete/brick/stone terracotta
/impervious asphalt
Open-set highrise
Txurdinaga 40 m 30 m 1.3 concrete/brick terracotta
/impervious asphalt
16
m
16m
24
m
4.5m
30m
40
m
Compact Lowrise
Compact Midrise
Open-set Highrise
Simulation analysis 76
Methodology
Reconciling Adaptation, Mitigation and Sustainable Development for Cities
• Analysis conducted using ENVImet.
• Meteorological parameters, albedo of the surface and solid angle proportion.
• Outputs Predicted Mean Vote (PMV), Physiological Equivalent Temperature (PET) to evaluate the thermal stress affecting the body;
• Building geometry/orientation, vegetation elements, urban parks, and street canyons;
• Analysis of urban thermal comfort and impact assessment of climate change scenarios in urban areas.
77 Source: http://www.envi-met.com/
Input for the ENVI-met simulations based on real data
Reconciling Adaptation, Mitigation and Sustainable Development for Cities
Start and duration of the model
Start Date of simulation (dd.mm.yyyy) Summer: 07.08.2010
Start time (hh:mm:ss) 04:00:00
Total simulation time (h) 44
Output settings
Receptors and buildings (min) 10 (output interval for files)
Initial meteorological conditions
Wind speed measured in 10 m height (m/s) 4.0 m/s
Wind direction (deg) 315 º (0º = from North …180º =from South…)
Initial temperature of atmosphere (°K) 293.44 ºK (20.29 ºC)
Relative humidity in 2 m height (%) 63.3
78 The weather data used to initiate the models were provided by the meteorological station of Deusto, which is located in the northern part of the city at 3 m above sea level (latitude 43.28N, longitude 2.93W)
Reconciling Adaptation, Mitigation and Sustainable Development for Cities
The study was conducted setting these local data
• Materials:
Facades: B2 - Brick wall (burned)
Roofs : R1 - Roofing: tile
• Soill:
Street : Asphalt/Brick red stones
Green areas: Loamy
• Vegetation:
Presence grass 50 cm average dense: 30% up to the total surface;
Trees: Tree 5m; 1/3 without leaves, Platanus 5m , Platanus 10m
Hypothesis
79
Scenarios 80
Reconciling Adaptation, Mitigation and Sustainable Development for Cities
S0
Initial
S1
Pedestrian
S2
Grass
S3
Grass + trees
S4
Green roofs
S5
Grass + green
roofs
S6
Grass + trees +
green roofs
Compact Lowrise 82
Scenarios of the Compact Lowrise urban areas
Reconciling Adaptation, Mitigation and Sustainable Development for Cities
83 S1 – Initial S2 – Grass S3 – Grass and Trees
S4 – Green roofs S5 – Grass and Green roofs
S6 – Grass, Trees and Green roofs
Compact Midrise 84
Scenarios of the Open set Highrise urban areas
Reconciling Adaptation, Mitigation and Sustainable Development for Cities
85 S0 and S1 Initial S2 – Grass S3 – Grass and Trees
S4 Green roofs
S5 – Grass and Green roofs
S6 – Grass, Trees and Green roofs
Open set Highrise 86
Results of the Open set High-rise urban areas
Reconciling Adaptation, Mitigation and Sustainable Development for Cities
87 S1 – Initial S2 – Grass S3 – Grass and Trees
S4 – Green roofs S5 – Grass and Green roofs
S6 – Grass, Trees and Green roofs
5 Others climate aspects Summer school SEniC 2015
Luca Italy
Gabriele Italy
Charles Sweden
Liu YuTing 刘昱婷
China
Xi Jia 席加 China
Wang Kun 王琨
China
Stergios Greece
Zhou LiWei 周丽薇 China
Li FangBing 李芳兵 China
Li WeiZhe 李玮哲 China
Yuan Chen 袁宸 China
Zhang ZhengYang 张正洋 China
Silvia Italy
Xiang Can 向璨 China
Li BoWen 李博文 China
Shimantika Bangladesh
Wang YuYuan 王钰圆 China
Shanghai, Zhoukanghang Six high rise residential buildings Height 50 m Volume 2400 m³/building Total volume 14400 m³
Site
Climate Climate
Temperature & Humidity
Temperature & Humidity Jun Jul Aug
Average Temp(℃)
23 27.5 27.7
Maximum Temp(℃)
31 35.5 38
Average RH(%)
83.54 81.21 77.90
Dec Jan Feb
Average Temp(℃)
6.5 4.3 6.1
Minimum Temp(℃)
-4.3 -8.7 -7.5
Average RH(%)
74.54 74.44 74.86
In summer, there are 48 days in which maximum temp is over 30 ℃. It’s comfortable in Jun and needs cooling in Jul and Aug.
In winter, there are 60 days in which minimum temp is below 10 ℃. We need heating in all these three months.
Climate
Climate
Winter Passive Strategies Summer Passive Strategies
Passive solar heating
Thermal mass
Shading
Natural ventilation
Passive solar heating
Key components: windows size, windows inclination, materials
Thermal mass
Key components: construction, materials
0%
100%
0%
100%
Jan Dec Year Jan Dec Year
Winter Passive Strategies
Shading
Key components: windows size & orientation and inclination, shading devices
Summer Passive Strategies
Natural Ventilation
Key components: windows size, windows distribution/orientation
0%
100%
Jan Dec Year 0%
100%
Jan Dec Year
Wind
Wind Speed & Direction
0
1
2
3
4
5
6
7
8
1 2 3 4 5 6 7 8 9 10 11 12
Wind Speed Avg Daily Winter Summer
Wind Direction
Northwest Southeast &
East
Range of Speed
10-40km/h 5-30km/h
Average Wind Speed
6.5m/s 6m/s
Winter Summer
Climate
Solar Radiation
Climate Radiation Angle
Apr May Jun July Aug Sept
Ranging Time (h)
10--16 10--16 9--17 7--18 7--18 9--17
Bearing Angle (°)
E67--W82 E80--W94 E95--W105
E105--W110
E95--W100
E68--W81
Altitude Angle (°)
55--68--32
58--75--35
48--81--24
19--75--12
17--68--6 38--53--
12
0 120 120 10
90
0 120 120 10
90
Jun Jul Aug Sep
Time we need shading (h)
9:00-17:00 7:00-19:00 9:00-17:00 11:00-15:00
Climate Sunlight Time - Shading
Air Pollution
Air Pollution
Wind from north-west and south-east bring more pollutant
Solar Analysis
Building 1-6 and 7-9 Solar Analysis
Model Created in Rhinoceros Environment
Solar Dynamic Simulation Conducted Using DIVA for Rhino in Isolated & Context Scenarios
Methodology Solar Analysis
Roof : F G H Facade: A B C D E
Roof
Facade
Solar Radiation
0
200
400
600
800
1000
1200
1
38
2
76
3
11
44
15
25
19
06
22
87
26
68
30
49
34
30
38
11
41
92
45
73
49
54
53
35
57
16
60
97
64
78
68
59
72
40
76
21
80
02
83
83
kWh
/m²
yr
Hours
0
100
200
300
400
500
600
700
13
66
73
11
09
61
46
11
82
62
19
12
55
62
92
13
28
63
65
14
01
64
38
14
74
65
11
15
47
65
84
16
20
66
57
16
93
67
30
17
66
68
03
18
39
6
kWh
/m²
yr
Hours
Decrease of Radiation Due to Surroundings
kWh/
m2
Building 1 Building 2 Building 3 Building 4 Building 5 Building 6
Isolated Context Isolated Context Isolated Context Isolated Context Isolated Context Isolated Context
Direct 27.3 23.3 27.6 23.7 27.6 27.1 26.7 25.0 27.5 26.2 27.6 27.1
Global 82.1 60.8 82.2 62.6 81.4 79.0 81.3 68.4 81.7 74.2 82.1 71.2
Diffuse 54.8 37.5 54.6 38.9 53.8 52.0 54.6 43.4 54.1 47.9 54.4 44.1
Direct 14.5% 14.1% 1.8% 6.4% 4.8% 1.8%
Global 25.9% 23.9% 2.9% 15.9% 9.2% 13.3%
Diffuse 31.6% 28.8% 3.4% 20.6% 11.4% 19.0%
The worst one The best one
Solar Radiation
Radiation Map and Overshadowing Effect Solar Radiation
Percentage Decrease Facade B ab=0
Roof 708 -1389 kWh/m2yr
Facade 73-281 kWh/m2yr
Hei
ght(
m)
Width(m)
24 m
Direct Component
Solar Radiation Roof
708 -1389 kWh/m2yr
Facade 195-805 kWh/m2yr
Hei
ght(
m)
Width(m)
32 m
Radiation Map and Overshadowing Effect
Percentage Decrease Facade B ab=1
Global Component
Optimized Orientation
New layout
Optimal orientation from solar analysis on Ecotect
Solar System 28°
• System: photovoltaic solar shading louvre (imput from group B – Professor Dai)
• Optimal inclination for the entire year: 28° (Data Source: Optimal tilt-angles for solar collectors used in China Runsheng Tang, Tong Wu)
• Solar analysis on DIVA for calculating the optimal distance between the louvres: 75 cm
Solar System
24 m
Current Design New Design
Wind Flow
• Wind speed less than 5m/s Below 1.5m
• In summer the pressure difference of front and back side of the
building has to be about 2 Pa to ensure enough natural ventilation
• In winter the pressure difference of front and back side of the building has to be less than 5 Pa (except for the first row of the buildings towards wind)
(Data Source: Green Building Evaluation Criteria & Ecological Residential Building Technology Assessment Manual of China)
Wind Flow Simulation Assessment Standards
SUMMER (Wind Direction: SE)
3m/s
3m/s
Wind Speed Close to 0 m/s Pressure Diff. 0-0.5 Pa
WINTER (Wind Direction: N)
Wind Speed Close to 0 m/s Pressure Diff. 0-0.5Pa
3m/s
3m/s
Old Layout
New Layout
SUMMER SE, 3 m/s
Wind Flow Simulation
Green Strategies
Results • Green integrated in the facade of
the building
• Green roof
Goals
– Reduces the overheating effects, resulting in the reduction of the heating load
– Filter the pollution from the air
– Reduce local air and ground temperature
– Improve of the environmental comfort of the construction site
Internal Layout
Mean Daylight Factor 2,47%
Daylight Autonomy 56%
Daylight Analysis
Modified Layout
Layout Improvements
Original Layout
We want to thank you all for the past two amazing weeks together!!!
NTNU#SmartCities
http://smartsustainablecities.org/
Gabriele Lobaccaro NTNU - Norwegian of Science and Technology